Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Whole Genome Sequencing of Bacillus safensis WOIS2 and Bacillus sp. WOD8, Nitrile-metabolizing Bacteria (NMB) isolated from Solid Waste Leachates in Lagos, Nigeria

PROVIDER: PRJNA1057587 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other
	SRR28408606.fastq.gz	Fastqsanger.gz

Items per page:

1 - 2 of 2

Similar Datasets

Nitrile-metabolizing Bacteria

Project description:Two nitrile-metabolizing bacteria isolated from two major landfills in Lagos, Nigeria Genome sequencing and assembly

| PRJNA1043449 | ENA

PyoLagos

Project description:Clinical Pseudomonas aeruginosa isolates from Lagos, Nigeria

| PRJEB59020 | ENA

Project description:Genome analysis of Vibrio metschnikovii strain MSAJ1-NIMR isolated from Lagos lagoon, Nigeria

| PRJNA1177791 | ENA

sediment metagenome

Project description:PAH-contaminated sediment from the Lagos Lagoon, Nigeria

| PRJNA310143 | ENA

Solid waste leachates

Project description:Metagenomic Analysis Displaying the Diverse Microbial Community of Two Major Waste Disposing Systems in Lagos, Nigeria

| PRJNA849224 | ENA

Project description:Physiological and ecological response of a simultaneous nitrification-denitrification process treating organic solid waste leachates

| PRJNA1190091 | ENA

Okuonghae2020 - SEAIR model of COVID-19 transmission in Lagos, Nigeria

Project description:This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first reported case on 16 March 2020, we seek to develop a predicative tool for the cumulative number of reported cases and the number of active cases in Lagos; we also estimate the basic reproduction number of the disease outbreak in the aforementioned State in Nigeria. Using numerical simulations, we show the effect of control measures, specifically the common social distancing, use of face mask and case detection (via contact tracing and subsequent testings) on the dynamics of COVID-19. We also provide forecasts for the cumulative number of reported cases and active cases for different levels of the control measures being implemented. Numerical simulations of the model show that if at least 55% of the population comply with the social distancing regulation with about 55% of the population effectively making use of face masks while in public, the disease will eventually die out in the population and that, if we can step up the case detection rate for symptomatic individuals to about 0.8 per day, with about 55% of the population complying with the social distancing regulations, it will lead to a great decrease in the incidence (and prevalence) of COVID-19.

2024-09-02 | BIOMD0000000991 | BioModels

landfill metagenome

Project description:Solid Waste Metagenome

| PRJNA382604 | ENA

Bacillus safensis

Project description:Bacillus safensis overview

| PRJNA163069 | ENA

Project description:Deciphering Soil Bacterial Community Structure of Lagos Mainland Waste Dump Sites, Nigeria: Insights on Potential Impacts of Different Pollutants from Municipal and Industrial Waste

| PRJNA540227 | ENA

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data